Predicting microRNA precursors with a generalized Gaussian components based density estimation algorithm

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) are short non-coding RNA molecules, which play an important role in post-transcriptional regulation of gene expression. There have been many efforts to discover miRNA precursors (pre-miRNAs) over the years. Recently, <it>ab initio </it>approaches have attracted more attention because they do not depend on homology information and provide broader applications than comparative approaches. Kernel based classifiers such as support vector machine (SVM) are extensively adopted in these <it>ab initio </it>approaches due to the prediction performance they achieved. On the other hand, logic based classifiers such as decision tree, of which the constructed model is interpretable, have attracted less attention.</p> <p>Results</p> <p>This article reports the design of a predictor of pre-miRNAs with a novel kernel based classifier named the generalized Gaussian density estimator (G²DE) based classifier. The G²DE is a kernel based algorithm designed to provide interpretability by utilizing a few but representative kernels for constructing the classification model. The performance of the proposed predictor has been evaluated with 692 human pre-miRNAs and has been compared with two kernel based and two logic based classifiers. The experimental results show that the proposed predictor is capable of achieving prediction performance comparable to those delivered by the prevailing kernel based classification algorithms, while providing the user with an overall picture of the distribution of the data set.</p> <p>Conclusion</p> <p>Software predictors that identify pre-miRNAs in genomic sequences have been exploited by biologists to facilitate molecular biology research in recent years. The G²DE employed in this study can deliver prediction accuracy comparable with the state-of-the-art kernel based machine learning algorithms. Furthermore, biologists can obtain valuable insights about the different characteristics of the sequences of pre-miRNAs with the models generated by the G²DE based predictor.</p

Study on the Correlation between Objective Evaluations and Subjective Speech Quality and Intelligibility

Subjective tests are the gold standard for evaluating speech quality and intelligibility, but they are time-consuming and expensive. Thus, objective measures that align with human perceptions are crucial. This study evaluates the correlation between commonly used objective measures and subjective speech quality and intelligibility using a Chinese speech dataset. Moreover, new objective measures are proposed combining current objective measures using deep learning techniques to predict subjective quality and intelligibility. The proposed deep learning model reduces the amount of training data without significantly impacting prediction performance. We interpret the deep learning model to understand how objective measures reflect subjective quality and intelligibility. We also explore the impact of including subjective speech quality ratings on speech intelligibility prediction. Our findings offer valuable insights into the relationship between objective measures and human perceptions

Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p

The global response: How cities and provinces around the globe tackled Covid-19 outbreaks in 2021

Background: Tackling the spread of COVID-19 remains a crucial part of ending the pandemic. Its highly contagious nature and constant evolution coupled with a relative lack of immunity make the virus difficult to control. For this, various strategies have been proposed and adopted including limiting contact, social isolation, vaccination, contact tracing, etc. However, given the heterogeneity in the enforcement of these strategies and constant fluctuations in the strictness levels of these strategies, it becomes challenging to assess the true impact of these strategies in controlling the spread of COVID-19.Methods: In the present study, we evaluated various transmission control measures that were imposed in 10 global urban cities and provinces in 2021 Bangkok, Gauteng, Ho Chi Minh City, Jakarta, London, Manila City, New Delhi, New York City, Singapore, and Tokyo.Findings: Based on our analysis, we herein propose the population-level Swiss cheese model for the failures and pit-falls in various strategies that each of these cities and provinces had. Furthermore, whilst all the evaluated cities and provinces took a different personalized approach to managing the pandemic, what remained common was dynamic enforcement and monitoring of breaches of each barrier of protection. The measures taken to reinforce the barriers were adjusted continuously based on the evolving epidemiological situation.Interpretation: How an individual city or province handled the pandemic profoundly affected and determined how the entire country handled the pandemic since the chain of transmission needs to be broken at the very grassroot level to achieve nationwide control

The approach of in-situ doping ion conductor fabricated with the cathodic arc plasma for all-solid-state electrochromic devices

The all-solid-state electrochromic device (ECD) with the one substrate structure fabricated by the reactive dc magnetron sputtering (DCMS) and in-situ doping cathodic vacuum arc plasma (CVAP) technology has been developed. The electrochromic (EC) layer and ion conductor layer were deposited by reactive DCMS and CVAP technology, respectively. The in-situ doping ion conductor Ta2O5 deposited by the CVAP technology has provided the better material structure for ion transportation and showed about 2 times ion conductivity than the external doping process. The all-solid-state ECD with the in-situ doping CVAP ion conductor layer has demonstrated a maximum transmittance variation (ΔT) of 71% at 550 nm, and a faster switching speed. The lower production cost and higher process stability could be achieved by the application of in-situ doping CVAP technology without breaking the vacuum process. Furthermore, the ion doping process with the reuse of energy during the CVAP process is not only decreasing the process steps, but also reducing the process energy consumption

Molecular Imaging of Ischemia and Reperfusion in Vivo with Mitochondrial Autofluorescence

Ischemia and reperfusion (IR) injury constitutes a pivotal mechanism of tissue damage in pathological conditions such as stroke, myocardial infarction, vascular surgery, and organ transplant. Imaging or monitoring of the change of an organ at a molecular level in real time during IR is essential to improve our understanding of the underlying pathophysiology and to guide therapeutic strategies. Herein, we report molecular imaging of a rat model of hepatic IR with the autofluorescence of mitochondrial flavins. We demonstrate a revelation of the histological characteristics of a liver in vivo with no exogenous stain and show that intravital autofluorescent images exhibited a distinctive spatiotemporal variation during IR. The autofluorescence decayed rapidly from the baseline immediately after 20-min ischemia (approximately 30% decrease in 5 min) but recovered gradually during reperfusion (to approximately 99% of the baseline 9 min after the onset of reperfusion). The autofluorescent images acquired during reperfusion correlated strongly with the reperfused blood flow. We show further that the autofluorescence was produced predominantly from mitochondria, and the distinctive autofluorescent variation during IR was mechanically linked to the altered balance between the flavins in the oxidized and reduced forms residing in the mitochondrial electron-transport chain. Our approach opens an unprecedented route to interrogate the deoxygenation and reoxygenation of mitochondria, the machinery central to the pathophysiology of IR injury, with great molecular specificity and spatiotemporal resolution and can be prospectively translated into a medical device capable of molecular imaging. We envisage that the realization thereof should shed new light on clinical diagnostics and therapeutic interventions targeting IR injuries of not only the liver but also other vital organs including the brain and heart

Photosynthesis in Response to Different Salinities and Immersions of Two Native Rhizophoraceae Mangroves

Mangrove ecosystems are vulnerable to rising sea levels as the plants are exposed to high salinity and tidal submergence. The ways in which these plants respond to varying salinities, immersion depths, and levels of light irradiation are poorly studied. To understand photosynthesis in response to salinity and submergence in mangroves acclimated to different tidal elevations, two-year-old seedlings of two native mangrove species, Kandelia obovata and Rhizophora stylosa, were treated at different salinity concentrations (0, 10, and 30 part per thousand, ppt) with and without immersion conditions under fifteen photosynthetic photon flux densities (PPFD &mu;mol photon&middot;m&minus;2&middot;s&minus;1). The photosynthetic capacity and the chlorophyll fluorescence (ChlF) parameters of both species were measured. We found that under different PPFDs, electron transport rate (ETR) induction was much faster than photosynthetic rate (Pn) induction, and Pn was restricted by stomatal conductance (Gs). The Pn of the immersed K. obovata plants increased, indicating that this species is immersed-tolerant, whereas the Pn level of the R. stylosa plants is salt-tolerant with no immersion. All of the plants treated with 30 ppt salinity exhibited lower Pn but higher non-photochemical quenching (NPQ) and heat quenching (D) values, followed by increases in the excess energy and photoprotective effects. Since NPQ or D can be easily measured in the field, these values provide a useful ecological monitoring index that may provide a reference for mangrove restoration, habitat creation, and ecological monitoring

Growth and Structure of ZnO Nanorods on a Sub-Micrometer Glass Pipette and Their Application as Intracellular Potentiometric Selective Ion Sensors

This paper presents the growth and structure of ZnO nanorods on a sub-micrometer glass pipette and their application as an intracellular selective ion sensor. Highly oriented, vertical and aligned ZnO nanorods were grown on the tip of a borosilicate glass capillary (0.7 µm in diameter) by the low temperature aqueous chemical growth (ACG) technique. The relatively large surface-to-volume ratio of ZnO nanorods makes them attractive for electrochemical sensing. Transmission electron microscopy studies show that ZnO nanorods are single crystals and grow along the crystal’s c-axis. The ZnO nanorods were functionalized with a polymeric membrane for selective intracellular measurements of Na+. The membrane-coated ZnO nanorods exhibited a Na+-dependent electrochemical potential difference versus an Ag/AgCl reference micro-electrode within a wide concentration range from 0.5 mM to 100 mM. The fabrication of functionalized ZnO nanorods paves the way to sense a wide range of biochemical species at the intracellular level